HR Planning Software

Azati audited and optimized an application for an international staffing agency. Critical issues were identified and resolved, resulting in enhanced performance, new features, and an improved user experience. These changes led to faster loading times and increased application stability, successfully stopping the decline in the user base.

Discuss an idea

All Technologies Used

Angular
Angular
JQuery
JQuery
Ruby
Ruby
PostgreSQL
PostgreSQL
Heroku
Heroku
Amazon Cloud Front
Amazon Cloud Front
Heroku CI
Heroku CI

Motivation

The customer, a well-known international staffing agency, aimed to audit and optimize the existing HR planning platform. The main goal was to address performance issues, stabilize the application, and create a roadmap for further improvements.

Main Challenges

Challenge 1
Bad Application Architecture

The initial solution lacked proper structure, relying on a mix of separate functions created with various paradigms.

Challenge 2
Outdated Technology Stack

The back-end was built with Ruby on Rails, and the front-end used Angular.js, resulting in an 18-second initial page load time.

Challenge 3
Lack of Automated Tests

The absence of unit and functional tests made it challenging to introduce new features without breaking existing functionality.

Challenge 4
Premade Package Overuse

Overreliance on Ruby Gems led to low performance and high memory consumption.

Key Features

  • Scalable Architecture: Reliable application architecture designed for long-term scalability and optimal performance under load.
  • Localization Support: Multilingual support implemented via i18n, enabling global reach through seamless localization.
  • SQL and Memory Optimization: Refactored SQL workflows and reduced memory consumption by 20%, improving overall efficiency.
  • Enhanced Front-End Performance: Implemented pagination and asset caching strategies to accelerate user-facing interactions.
  • Automated Quality Assurance: Introduced automated test coverage for critical application logic, reducing regression risks.

Our Approach

Audit and Issue Prioritization
Conducted a thorough audit to identify and prioritize critical issues.
Back-End Performance Optimization
Optimized back-end performance by refactoring code, simplifying architecture, and reducing dependency on unnecessary packages.
SQL Query Optimization
Implemented complex SQL queries to reduce database call chains and speed up data extraction.
Front-End Enhancement
Enhanced the front-end by improving load times, introducing pagination, and optimizing caching.
Multilingual Support Implementation
Delivered multilingual support to expand the platform's accessibility to users in France and Germany.

Project Impact

Faster Page Loads: Initial page load time reduced dramatically — from 18 seconds to under 3 seconds, improving user experience.

Improved Back-End Efficiency: Back-end performance increased by 43%, allowing the system to handle more concurrent users.

Lower Resource Usage: RAM consumption was reduced by 20%, lowering infrastructure costs and improving stability.

Higher User Satisfaction: Performance improvements stabilized the customer base and increased user confidence in the platform.

Ready To Get Started

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.